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743 items in total found

Journal Articles | 2019

Modeling a decision-maker's choice behavior through perceived values

Manish Aggarwal

IEEE Transactions on Systems, Man, and Cybernetics: Systems

In the real world, an attribute value is perceived differently by different individuals. Emphasizing on this aspect, we extend the discrete choice models with perceived values that are subjective and specific to a decision-maker (DM). The proposed choice models are augmented with the parameters of an entropy function, besides the utility coefficients, to model a DM's complex choice behavior. A variety of higher order choice models are also proposed. The proposed models are further extended with a DM's reference-value for each attribute. A real and illustrative application is included.

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Journal Articles | 2019

Logit Choice Models for Interactive Attributes

Manish Aggarwal

Information Sciences

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Journal Articles | 2019

Extended hesitant fuzzy linguistic term set with fuzzy confidence for solving group decision-making problems

R Krishankumar, K S Ravichandran, Manish Aggarwal, and Sanjay K Tyagi

Neural Computing and Applications

This paper presents a new extension of the hesitant fuzzy linguistic term set (HFLTS) called intuitionistic fuzzy confidence-based HFLTS that associates an intuitionistic fuzzy value (IFV) with each linguistic term. The resulting term set is termed as intuitionistic fuzzy confidence hesitant fuzzy linguistic term set (IFCHFLTS). The previous studies on the linguistic decision making have emphasized little upon the preference and non-preference for each of the linguistic terms. This information, however, is crucial in multi-criteria decision making under uncertainty. In this regard, we find IFV particularly useful for qualifying each of the linguistic terms with the agent’s degree of preference, non-preference, and hesitation values. Besides, a new aggregation operator named intuitionistic fuzzy confidence linguistic simple weighted geometry (IFCLSWG) is also proposed to fuse decision makers’ linguistic preferences. Further, the criteria weights are estimated using a new method called intuitionistic fuzzy confidence linguistic standard variance. An approach is also suggested for ranking the given alternatives by adapting VIKOR under the proposed IFCHFLTS context. Finally, the practicality and usefulness of the proposal are demonstrated through two real-world problems in green supplier selection for manufacturing industry, and medical diagnosis. The strengths and weaknesses of the proposal are also highlighted by drawing upon a comparison with similar methods.

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Journal Articles | 2019

Bridging the gap between probabilistic and fuzzy entropy

Manish Aggarwal

IEEE Transactions on Fuzzy Systems

The real world decision-making often involves a comparison of uncertain systems, or alternatives based on fuzzy evaluations. The concept of fuzzy entropy is quite useful in such situations. This paper critically examines the existing fuzzy entropy functions, and redefine them to add to their usefulness as measures of the fuzzy uncertainty in decision-making applications. More specifically, new variants of the extant Luca & Termini, and Pal & Pal fuzzy entropy functions are proposed. The proposed fuzzy entropy functions are extended for the probabilistic-fuzzy uncertainty, commonly observed in the real world. A real application is included to demonstrate the usefulness of the proposed entropy functions in decision-making applications.

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Journal Articles | 2019

Reforming agricultural markets in India: A tale of two model Acts

Sukhpal Singh

Economic & Political Weekly

The union Ministry of Agriculture and Farmers’ Welfare had prescribed a model Agricultural Produce Marketing Committee Act in 2003. The state-level adoption of the act has been tardy and varied in terms of both the magnitude and content of agricultural market reforms. Yet, the ministry under the current central government has come up with another model act, the Agricultural Produce and Livestock Marketing (Promotion and Facilitation) Act, 2017, supposedly an improvement over the 2003 act. Among other things, the provision that has grabbed much attention is the removal of contract farming from the APMC domain to a separate model act of Agricultural Produce and Livestock Contract Farming and Services (Promotion and Facilitation). Analysing these draft acts, the paper finds that both the model acts suffer from serious conceptual lacunae that have implications for their application and governance, and, consequently, for inclusive and sustainable agricultural development.

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Journal Articles | 2019

Impostor phenomenon in STEM: occurrence, attribution, and identity

Devasmita Chakraverty

Studies in Graduate and Postdoctoral Education

Purpose

This study aims to explore different themes related to impostor phenomenon, as experienced by graduate students and postdocs in science, technology, engineering and mathematics (STEM) fields.

Design/methodology/approach

Open-ended survey responses from 120 US-based participants from 40 states and Washington, D.C., describing an occasion when they felt like an impostor, were analyzed thematically.

Findings

Following content analysis, three themes emerged: occurrence, attribution and identity. While impostor-like feelings were experienced as early as high school or college, the majority experienced it during PhD application, on being admitted to a PhD program and throughout PhD training. The people experiencing impostor phenomenon attributed their achievements and success to others (other’s name, prestige, or connections, other’s mistake, other’s lies or misrepresentation, or other’s kindness) or self (self-inadequacy, pretense, luck or self-doubt) rather than their own hard work or ability. Gender-based and race/ethnicity-based identity also shaped the experiences of the impostor phenomenon.

Research limitations/implications

Open-ended survey responses varied in length and level of detail. Responses provided a one-time snapshot of a memory related to impostor-feelings that stood out, not indicating if the feeling persisted or evolved with time. The findings are not generalizable over a larger population.

Originality/value

This study identified multiple themes related to the impostor phenomenon not investigated before, enriching existing research while also providing methodological rigor for the development of follow-up studies.

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Journal Articles | 2019

Adapting the women's empowerment in agriculture index to specific country context: Insights and critiques from fieldwork in India

Soumya Gupta, Dhiraj Singh, Prabhu Pingali, and Vidya Vemireddy

Global Food Security

The Women's Empowerment in Agriculture Index (WEAI) is a direct, multi-dimensional measure of women's access to resources and decision-making in various domains of agriculture. However, several challenges characterize its use: adaptation of questionnaires to local agricultural contexts, modifications to index construction once underlying activities and adequacy thresholds are modified, and sensitivity analysis. In this paper, we address such challenges based on our experience of adapting and using the WEAI across 3600 households in India. In doing so we contribute to the methodological and technical base underlying the index, expand the WEAI evidence base for South Asia, and highlight the importance of tailoring the index to specific agricultural contexts in order to impact public policies in a meaningful way.

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Journal Articles | 2019

Estimation of log-odds ratio from group testing data using Firth correction

Surupa Roy and Tathagata Banerjee

Biometrical Journal: Journal of Mathematical Methods in Biosciences

We consider the estimation of the prevalence of a rare disease, and the log-odds ratio for two specified groups of individuals from group testing data. For a low-prevalence disease, the maximum likelihood estimate of the log-odds ratio is severely biased. However, Firth correction to the score function leads to a considerable improvement of the estimator. Also, for a low-prevalence disease, if the diagnostic test is imperfect, the group testing is found to yield more precise estimate of the log-odds ratio than the individual testing.

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Journal Articles | 2019

Regression models for group testing: Identifiability and asymptotics

Arindam Chatterjee and Tathagata Bandyopadhyay

Journal of Statistical Planning and Inference

Group testing has been widely used in epidemiology and related fields to estimate prevalence of rare diseases. Parametric binary regression models are used in group testing to estimate the covariate adjusted prevalence. Unlike the standard binary regression model (viz., logistic, complementary log–log, etc.), the regression model for group testing data connects the maximum of a group of independent binary responses to its covariate values. Recently, in group testing literature, it has been extensively used for estimating covariate adjusted prevalence of a disease making the tacit assumptions that (i) the regression model is identifiable, and (ii) the standard asymptotic theory is valid for the maximum likelihood estimators of the regression parameters. Verifying these assumptions is found to be non-trivial theoretical issues. In this paper, we give theoretical proofs of these assumptions under a set of simple sufficient conditions, thus, providing a theoretical justification for likelihood based inference on the regression parameters. We also provide an outline of the proof extending the asymptotic theory to the data obtained by Dorfman retesting, where all subjects in a positive group are retested.

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Journal Articles | 2019

On robust estimates of correlated risk in cyber-insured IT firms: A first look at optimal AI-based estimates under “Small” data

Ranjan Pal, Leana Golubchik, Konstanations Psounis, and Tathagata Bandyopadhyay

ACM Transactions on Management Information Systems

In this article, we comment on the drawbacks of the existing AI-based Bayesian network (BN) cyber-vulnerability analysis (C-VA) model proposed in Mukhopadhyay et al. (2013) to assess cyber-risk in IT firms, where this quantity is usually a joint distribution of multiple risk (random) variables (e.g., quality of antivirus, frequency of monitoring, etc.) coming from heterogeneous distribution families. As a major modeling drawback, Mukhopadhyay et al. (2013) assume that any pair of random variables in the BN are linearly correlated with each other. This simplistic assumption might not always hold true for general IT organizational environments. Thus, the use of the C-VA model in general will result in loose estimates of correlated IT risk and will subsequently affect cyber-insurance companies in framing profitable coverage policies for IT organizations. To this end, we propose methods to (1) find a closed-form expression for the maximal correlation arising between pairs of discrete random variables, whose value finds importance in getting robust estimates of copula-induced computations of organizational cyber-risk, and (2) arrive at a computationally effective mechanism to compute nonlinear correlations among pairs of discrete random variables in the correlation matrix of the CBBN model (Mukhopadhyay et al. 2013). We also prove that an empirical computation of MC using our method converges rapidly, that is, exponentially fast, to the true correlation value in the number of samples. Our proposed method contributes to a tighter estimate of IT cyber-risk under environments of low-risk data availability and will enable insurers to better assess organizational risks and subsequently underwrite profitable cyber-insurance policies.

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